Distinguishing Between Cyclical Changes And Structural In Economic Statistics

If we’ve got some nice little statistic that will give us advance warning of economic changes then we’re in clover. We go calculate that number, making sure we do so a coupe of days before everyone else, position our investments the right way and in time we’ll make Warren Buffett look like the pauper he should be.

We actually see examples of this. Current GDP statistics are a reasonably good indicator of what next month/quarter is going to look like. So, we all await with bated breath the official GDP stats from Census or ONS. But we can do better than that. We could, for example, go ask all the purchasing managers what they’re currently buying to make stuff with next quarter/month. And we could make sure we calculate this a couple of days before GDP comes out.

Yes, this works, the first variable in GDP is stocking for future production. We clean up therefore by buying access to the PMI indices from IHS Markit. But now everyone knows that GDP moves markets, also that PMI predicts so PMI moves markets. Thus we go buy the SMI data published by World Economy. Who are the peeps who used to write the PMI but sold up and started again. Oh, and their data comes out 2 days before the PMI stuff.

So far it all sounds a bit silly but it does work:

[perfectpullquote align=”full” bordertop=”false” cite=”” link=”” color=”” class=”” size=””] A significant and awful warning sign. Except, except…it’s important for us to understand why. In economics we really do have to grasp the difference between cyclical changes and structural ones. Imagine that we are trying to time the business cycle – and often we are. Looking at stats which change with the business cycle is obviously going to be helpful. But what if a change in our target statistic is about a structural change in the economy, not as more usual with this particular number, something cyclical? Which is what we’ve got here – a structural change in US corporate cash holdings [/perfectpullquote]

Except when it doesn’t. The usual reason it doesn’t being that what we thought was a purely cyclical variable turns out to now have varied for structural reasons. In this particular example, nonfinancial corporate debt to GDP ratio. It’s up at levels normally seen in the depth of a recession. But as you’ll have noted, we’re not in a recession. The actual reason why is Trump’s tax changes.

It really is important to differentiate between cyclical and structural reasons for a statistic.